Pixel & feature level multi-resolution image fusion based on fuzzy logic

Authors:
Bushra N. Kayani;Anwar M. Mirza;Haroon Iftikhar
Affiliations:
Faculty of Computer Science, GIK Institute of Engineering Sciences & Technology, Topi, Pakistan;Department of Computer Science, National University, Islamabad, Pakistan;Department of Electrical Engineering, University of Ottawa, Ottawa, Canada
Venue:
WAMUS'06 Proceedings of the 6th WSEAS international conference on Wavelet analysis & multirate systems
Year:
2006

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Abstract

The motivation behind fusing multi-resolution images is to create a single image with improved interpretability. In algorithm (based on pixel and feature level) presented in this paper, images are first segmented into regions with fuzzy clustering and are then fed into a fusion system, based on fuzzy if-then rules. Fuzzy clustering offers more flexibility over strict clustering; thus allowing more robustness as compared to other segmentation techniques (e.g. K-means clustering algorithm). A recently proposed subjective image fusion performance/quality evaluation measure known as IQI (Image Quality Index) [1] is used to measure the quality of the fused image. Results and conclusion outlined in this paper would help explain how well the proposed algorithm performs.